Short answer
Hosted APIs such as OpenAI, Anthropic Claude or Google Gemini offer top quality with no infrastructure, paid per token, and suit most products starting out. Open-weight models such as Llama, Mistral or Qwen run on your own servers or private cloud, giving data control, predictable costs at high volume and fine-tuning freedom, but need GPU hosting and engineering. Start with an API; self-host when needed.
Updated · Written by the Infikey Technologies delivery team
Choose Hosted API if…
You want the best quality quickly, volumes are moderate, and your data can be processed by a provider under its business terms.
Choose Open-source LLM if…
Data must stay on your infrastructure, volumes are high enough that per-token costs hurt, or you need deep fine-tuning or offline use.
Comparison
| Factor | Hosted API (OpenAI and others) | Open-source / open-weight LLM |
|---|---|---|
| Quality | Leading models for reasoning and coding | Strong and improving; best open models close the gap for many tasks |
| Setup | API key and code | GPU servers or managed hosting, model serving |
| Cost model | Per token, scales with use | Infrastructure cost, flat at steady volume |
| Data privacy | Provider terms; API data is not used for training by default at major providers | Data stays on your infrastructure |
| Customisation | Prompting, retrieval, some fine-tuning | Full fine-tuning and control |
| Maintenance | Provider updates models | You update and monitor |
Retrieval matters more than the model
For business assistants, answer quality depends mostly on retrieval-augmented generation (RAG): finding the right documents and passing them to the model. A well-built RAG system works with either option and lets you switch models later. Estimate costs with the RAG AI assistant cost calculator and the LLM token cost calculator.
Where we see each used
- Customer support and sales chatbots usually start on hosted APIs; see the AI chatbot cost calculator.
- Hospitals, lenders and insurers often prefer private deployments for sensitive data; see the healthcare, fintech and insurance guides.